As an image processing technique, an edge preserving smoothing processing is known. The edge preserving smoothing processing is nonlinear filter processing performed for smoothing tone while considerable differences of luminance-levels in boundaries between objects in an image remain. The edge preserving smoothing processing has been used through the ages in noise reduction processing for removing small variation of luminance while contours of objects which affect visibility are preserved (refer to Non-Patent Documents 1 to 3, for example).
Furthermore, the edge preserving smoothing processing is also used in tone correction processing in which, while detail components, such as texture, are not changed, luminance-level differences among other components are compressed by making use of a characteristic in which small luminance variation of texture of an object and a luminance-level difference can be separated from each other (refer to Non-Patent Document No. 4 and 5).
In such edge preserving smoothing processing, in recent years, a technique referred to as a bilateral filter has been often used. In general, in a bilateral filter BLF(pc) for images, as shown in equation (1), a calculation in which a pixel value I(p) of a pixel positioned in the vicinity of a pixel position pc which has been weighted by a weight function ω (p−pc) in a spatial direction and a weight function φ(I(p)−I(pc)) in a luminance-value direction is added is performed.
                    Equation        ⁢                                  ⁢                  (          1          )                                                                              BLF          ⁡                      (            pc            )                          =                                            ∑                              p                ∈                Ω                                      ⁢                                                  ⁢                                          ω                ⁡                                  (                                      p                    -                    pc                                    )                                            ·                              ϕ                ⁡                                  (                                                            I                      ⁡                                              (                        p                        )                                                              -                                          I                      ⁡                                              (                        pc                        )                                                                              )                                            ·                              I                ⁡                                  (                  p                  )                                                                                        ∑                              p                ∈                Ω                                      ⁢                                                  ⁢                                          ω                ⁡                                  (                                      p                    -                    pc                                    )                                            ·                              ϕ                ⁡                                  (                                                            I                      ⁡                                              (                        p                        )                                                              -                                          I                      ⁢                                              (                        pc                        )                                                                              )                                                                                        (        1        )            
Note that, in equation (1), a denominator on the right-hand side denotes a normalized coefficient. Non-Patent Document 4 discloses a technique of tone correction processing employing such a bilateral filter.
As shown in equation (1), in the bilateral filter, the weighting on pixels p included in a local region changes depending on luminance values of center pixels pc. Therefore, a weight value should be recalculated for each pixel, and accordingly, an amount of operation becomes larger than that required for a normal linear FIR (Finite Impulse Response) filter, for example. In Non-Patent Documents 4 and 6, to address such a disadvantage of bilateral filters, methods for increasing a calculation speed of a bilateral filter have been disclosed.    NON-Patent Document 1: A. Lev, S. W. Zucker, A. Rosenfeld, “Iterative enhancement of noise images”, IEEE Trans. Systems, Man, and Cybernetics, Vol. SMC-7, 1977.    NON-Patent Document 2: D. C. C. Wang, A. H. Vagnucci, C. C. Li, “Gradient inverse weighted smoothing scheme and the evaluation of its performance”, CVGIP, Vol. 15, pp. 167-181, 1981.    NON-Patent Document 3: M. Nagao, T. Matsuyama, “Edge preserving smoothing”, CGIP, Vol. 9, pp. 394-407, 1978.    NON-Patent Document 4: F. Durand, J. Dorsey, “Fast bilateral filtering for the display of high-dynamic-range images”, Proc. of ACM SIGGRAPH 2002, 2002.    NON-Patent Document 5: S. N. Pattanaik, H. Yee, “Adaptive gain control for high dynamic range image display”, Proc. of Spring Conference in Computer Graphics 2002, 2002.    NON-Patent Document 6: Weiss, “Fast median and bilateral filtering”, Proc. of ACM SIGGRAPH 2006, 2006.